Dataset statistics
| Number of variables | 15 |
|---|---|
| Number of observations | 12500 |
| Missing cells | 11571 |
| Missing cells (%) | 6.2% |
| Duplicate rows | 147 |
| Duplicate rows (%) | 1.2% |
| Total size in memory | 1.4 MiB |
| Average record size in memory | 120.0 B |
Variable types
| NUM | 11 |
|---|---|
| CAT | 4 |
Reproduction
| Analysis started | 2020-07-12 19:23:04.073872 |
|---|---|
| Analysis finished | 2020-07-12 19:23:26.867265 |
| Duration | 22.79 seconds |
| Version | pandas-profiling v2.8.0 |
| Command line | pandas_profiling --config_file config.yaml [YOUR_FILE.csv] |
| Download configuration | config.yaml |
| Dataset has 147 (1.2%) duplicate rows | Duplicates |
quarter has a high cardinality: 100 distinct values | High cardinality |
city has a high cardinality: 346 distinct values | High cardinality |
heating_type has a high cardinality: 54 distinct values | High cardinality |
latitude is highly correlated with lambert_poistion_y | High correlation |
lambert_poistion_y is highly correlated with latitude | High correlation |
longitude is highly correlated with lambert_poistion_x | High correlation |
lambert_poistion_x is highly correlated with longitude | High correlation |
construction_year has 2610 (20.9%) missing values | Missing |
heating_type has 913 (7.3%) missing values | Missing |
number_of_bedrooms has 7722 (61.8%) missing values | Missing |
living_space
Real number (ℝ≥0)
| Distinct count | 3428 |
|---|---|
| Unique (%) | 27.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 85.66294079999999 |
|---|---|
| Minimum | 13.2 |
| Maximum | 326.4 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 13.2 |
|---|---|
| 5-th percentile | 40.8 |
| Q1 | 62.4 |
| median | 79.2 |
| Q3 | 100.8 |
| 95-th percentile | 152.7048 |
| Maximum | 326.4 |
| Range | 313.2 |
| Interquartile range (IQR) | 38.4 |
Descriptive statistics
| Standard deviation | 35.87666723 |
|---|---|
| Coefficient of variation (CV) | 0.4188119961 |
| Kurtosis | 4.229907393 |
| Mean | 85.6629408 |
| Median Absolute Deviation (MAD) | 18.768 |
| Skewness | 1.540084489 |
| Sum | 1070786.76 |
| Variance | 1287.135252 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 72 | 224 | 1.8% | |
| 60 | 194 | 1.6% | |
| 78 | 187 | 1.5% | |
| 66 | 177 | 1.4% | |
| 96 | 159 | 1.3% | |
| 84 | 156 | 1.2% | |
| 90 | 147 | 1.2% | |
| 54 | 143 | 1.1% | |
| 74.4 | 133 | 1.1% | |
| 62.4 | 128 | 1.0% | |
| Other values (3418) | 10852 | 86.8% |
| Value | Count | Frequency (%) | |
| 13.2 | 1 | < 0.1% | |
| 14.4 | 1 | < 0.1% | |
| 15.612 | 1 | < 0.1% | |
| 16.8 | 3 | < 0.1% | |
| 16.968 | 1 | < 0.1% |
| Value | Count | Frequency (%) | |
| 326.4 | 1 | < 0.1% | |
| 320.4 | 1 | < 0.1% | |
| 318 | 2 | < 0.1% | |
| 310.176 | 1 | < 0.1% | |
| 300 | 1 | < 0.1% |
rooms
Real number (ℝ≥0)
| Distinct count | 18 |
|---|---|
| Unique (%) | 0.1% |
| Missing | 6 |
| Missing (%) | < 0.1% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 2.997702897390748 |
|---|---|
| Minimum | 1.5 |
| Maximum | 9.0 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 1.5 |
|---|---|
| 5-th percentile | 1.5 |
| Q1 | 2.5 |
| median | 3 |
| Q3 | 3.5 |
| 95-th percentile | 4.5 |
| Maximum | 9 |
| Range | 7.5 |
| Interquartile range (IQR) | 1 |
Descriptive statistics
| Standard deviation | 0.9339657431 |
|---|---|
| Coefficient of variation (CV) | 0.3115604765 |
| Kurtosis | 1.702485948 |
| Mean | 2.997702897 |
| Median Absolute Deviation (MAD) | 0.5 |
| Skewness | 0.7435259188 |
| Sum | 37453.3 |
| Variance | 0.8722920094 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 2.5 | 4460 | 35.7% | |
| 3.5 | 3685 | 29.5% | |
| 1.5 | 1398 | 11.2% | |
| 4.5 | 977 | 7.8% | |
| 3 | 947 | 7.6% | |
| 2 | 327 | 2.6% | |
| 4 | 313 | 2.5% | |
| 5.5 | 186 | 1.5% | |
| 5 | 103 | 0.8% | |
| 6.5 | 44 | 0.4% | |
| Other values (8) | 54 | 0.4% |
| Value | Count | Frequency (%) | |
| 1.5 | 1398 | 11.2% | |
| 2 | 327 | 2.6% | |
| 2.5 | 4460 | 35.7% | |
| 2.7 | 7 | 0.1% | |
| 3 | 947 | 7.6% |
| Value | Count | Frequency (%) | |
| 9 | 2 | < 0.1% | |
| 8.5 | 4 | < 0.1% | |
| 8 | 4 | < 0.1% | |
| 7.5 | 10 | 0.1% | |
| 7 | 6 | < 0.1% |
cold_rent
Real number (ℝ≥0)
| Distinct count | 3473 |
|---|---|
| Unique (%) | 27.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 1043.16407616 |
|---|---|
| Minimum | 159.6 |
| Maximum | 4788.0 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 159.6 |
|---|---|
| 5-th percentile | 438 |
| Q1 | 658.8 |
| median | 883.974 |
| Q3 | 1267.5 |
| 95-th percentile | 2162.232 |
| Maximum | 4788 |
| Range | 4628.4 |
| Interquartile range (IQR) | 608.7 |
Descriptive statistics
| Standard deviation | 580.8369474 |
|---|---|
| Coefficient of variation (CV) | 0.5568030578 |
| Kurtosis | 5.61917215 |
| Mean | 1043.164076 |
| Median Absolute Deviation (MAD) | 282.156 |
| Skewness | 1.947609099 |
| Sum | 13039550.95 |
| Variance | 337371.5595 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 720 | 164 | 1.3% | |
| 660 | 160 | 1.3% | |
| 780 | 148 | 1.2% | |
| 600 | 145 | 1.2% | |
| 900 | 145 | 1.2% | |
| 840 | 129 | 1.0% | |
| 1020 | 128 | 1.0% | |
| 1440 | 122 | 1.0% | |
| 960 | 121 | 1.0% | |
| 1140 | 104 | 0.8% | |
| Other values (3463) | 11134 | 89.1% |
| Value | Count | Frequency (%) | |
| 159.6 | 1 | < 0.1% | |
| 193.296 | 2 | < 0.1% | |
| 194.7 | 1 | < 0.1% | |
| 199.236 | 1 | < 0.1% | |
| 202.764 | 1 | < 0.1% |
| Value | Count | Frequency (%) | |
| 4788 | 2 | < 0.1% | |
| 4740 | 1 | < 0.1% | |
| 4680 | 1 | < 0.1% | |
| 4668 | 1 | < 0.1% | |
| 4654.8 | 1 | < 0.1% |
| Distinct count | 156 |
|---|---|
| Unique (%) | 1.6% |
| Missing | 2610 |
| Missing (%) | 20.9% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 1975.2360970677453 |
|---|---|
| Minimum | 1622.0 |
| Maximum | 2023.0 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 1622 |
|---|---|
| 5-th percentile | 1905 |
| Q1 | 1958 |
| median | 1974 |
| Q3 | 2010 |
| 95-th percentile | 2022 |
| Maximum | 2023 |
| Range | 401 |
| Interquartile range (IQR) | 52 |
Descriptive statistics
| Standard deviation | 36.95557882 |
|---|---|
| Coefficient of variation (CV) | 0.0187094489 |
| Kurtosis | 2.987460442 |
| Mean | 1975.236097 |
| Median Absolute Deviation (MAD) | 26 |
| Skewness | -0.8917614611 |
| Sum | 19535085 |
| Variance | 1365.714806 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 2022 | 395 | 3.2% | |
| 2020 | 349 | 2.8% | |
| 2021 | 320 | 2.6% | |
| 1904 | 294 | 2.4% | |
| 2019 | 242 | 1.9% | |
| 1964 | 232 | 1.9% | |
| 2018 | 211 | 1.7% | |
| 1959 | 206 | 1.6% | |
| 2023 | 198 | 1.6% | |
| 1960 | 179 | 1.4% | |
| Other values (146) | 7264 | 58.1% | |
| (Missing) | 2610 | 20.9% |
| Value | Count | Frequency (%) | |
| 1622 | 1 | < 0.1% | |
| 1648 | 1 | < 0.1% | |
| 1662 | 3 | < 0.1% | |
| 1668 | 1 | < 0.1% | |
| 1724 | 1 | < 0.1% |
| Value | Count | Frequency (%) | |
| 2023 | 198 | 1.6% | |
| 2022 | 395 | 3.2% | |
| 2021 | 320 | 2.6% | |
| 2020 | 349 | 2.8% | |
| 2019 | 242 | 1.9% |
| Distinct count | 100 |
|---|---|
| Unique (%) | 0.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 97.7 KiB |
| Winterhude | 642 |
|---|---|
| Rahlstedt | 529 |
| Barmbek-Nord | 403 |
| Wandsbek | 380 |
| Eimsbüttel | 358 |
| Other values (95) |
| Value | Count | Frequency (%) | |
| Winterhude | 642 | 5.1% | |
| Rahlstedt | 529 | 4.2% | |
| Barmbek-Nord | 403 | 3.2% | |
| Wandsbek | 380 | 3.0% | |
| Eimsbüttel | 358 | 2.9% | |
| Barmbek-Süd | 324 | 2.6% | |
| Harburg | 322 | 2.6% | |
| Langenhorn | 320 | 2.6% | |
| Eppendorf | 299 | 2.4% | |
| Niendorf | 289 | 2.3% | |
| Other values (90) | 8634 | 69.1% |
Length
| Max length | 20 |
|---|---|
| Median length | 9 |
| Mean length | 9.6124 |
| Min length | 4 |
| Distinct count | 7479 |
|---|---|
| Unique (%) | 60.2% |
| Missing | 80 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 565.6875201288245 |
|---|---|
| Minimum | -17044.0 |
| Maximum | 19121.0 |
| Zeros | 2 |
| Zeros (%) | < 0.1% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | -17044 |
|---|---|
| 5-th percentile | -9071.6 |
| Q1 | -2851 |
| median | 413 |
| Q3 | 3975 |
| 95-th percentile | 10800 |
| Maximum | 19121 |
| Range | 36165 |
| Interquartile range (IQR) | 6826 |
Descriptive statistics
| Standard deviation | 5827.887744 |
|---|---|
| Coefficient of variation (CV) | 10.3023092 |
| Kurtosis | 0.3385108086 |
| Mean | 565.6875201 |
| Median Absolute Deviation (MAD) | 3391.5 |
| Skewness | 0.0272276914 |
| Sum | 7025839 |
| Variance | 33964275.55 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 1032 | 35 | 0.3% | |
| 481 | 29 | 0.2% | |
| 44 | 28 | 0.2% | |
| 10252 | 26 | 0.2% | |
| -278 | 20 | 0.2% | |
| 1314 | 20 | 0.2% | |
| -321 | 20 | 0.2% | |
| 1023 | 20 | 0.2% | |
| 13232 | 18 | 0.1% | |
| 13386 | 16 | 0.1% | |
| Other values (7469) | 12188 | 97.5% | |
| (Missing) | 80 | 0.6% |
| Value | Count | Frequency (%) | |
| -17044 | 1 | < 0.1% | |
| -16743 | 1 | < 0.1% | |
| -16732 | 1 | < 0.1% | |
| -16716 | 1 | < 0.1% | |
| -16706 | 1 | < 0.1% |
| Value | Count | Frequency (%) | |
| 19121 | 1 | < 0.1% | |
| 18366 | 1 | < 0.1% | |
| 18307 | 1 | < 0.1% | |
| 18099 | 1 | < 0.1% | |
| 17493 | 1 | < 0.1% |
| Distinct count | 7155 |
|---|---|
| Unique (%) | 57.6% |
| Missing | 80 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 2622120.1461352655 |
|---|---|
| Minimum | 2603521.0 |
| Maximum | 2637566.0 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 2603521 |
|---|---|
| 5-th percentile | 2609967.7 |
| Q1 | 2620085 |
| median | 2622925.5 |
| Q3 | 2625299.25 |
| 95-th percentile | 2630694.25 |
| Maximum | 2637566 |
| Range | 34045 |
| Interquartile range (IQR) | 5214.25 |
Descriptive statistics
| Standard deviation | 5687.424428 |
|---|---|
| Coefficient of variation (CV) | 0.002169017479 |
| Kurtosis | 0.5514456637 |
| Mean | 2622120.146 |
| Median Absolute Deviation (MAD) | 2620.5 |
| Skewness | -0.6767508838 |
| Sum | 3.256673222e+10 |
| Variance | 32346796.62 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 2619709 | 33 | 0.3% | |
| 2619599 | 29 | 0.2% | |
| 2633517 | 29 | 0.2% | |
| 2628199 | 26 | 0.2% | |
| 2620710 | 24 | 0.2% | |
| 2625135 | 23 | 0.2% | |
| 2619416 | 21 | 0.2% | |
| 2612553 | 20 | 0.2% | |
| 2619187 | 19 | 0.2% | |
| 2631720 | 18 | 0.1% | |
| Other values (7145) | 12178 | 97.4% | |
| (Missing) | 80 | 0.6% |
| Value | Count | Frequency (%) | |
| 2603521 | 1 | < 0.1% | |
| 2603546 | 1 | < 0.1% | |
| 2603650 | 1 | < 0.1% | |
| 2603773 | 1 | < 0.1% | |
| 2604153 | 1 | < 0.1% |
| Value | Count | Frequency (%) | |
| 2637566 | 1 | < 0.1% | |
| 2637508 | 1 | < 0.1% | |
| 2637404 | 1 | < 0.1% | |
| 2637342 | 1 | < 0.1% | |
| 2637341 | 1 | < 0.1% |
| Distinct count | 346 |
|---|---|
| Unique (%) | 2.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 97.7 KiB |
| Hamburg | |
|---|---|
| Hamburg, HafenCity | 57 |
| Hamburg-Winterhude | 32 |
| Hamburg-Barmbek | 17 |
| Hamburg-Hamm | 17 |
| Other values (341) | 813 |
| Value | Count | Frequency (%) | |
| Hamburg | 11564 | 92.5% | |
| Hamburg, HafenCity | 57 | 0.5% | |
| Hamburg-Winterhude | 32 | 0.3% | |
| Hamburg-Barmbek | 17 | 0.1% | |
| Hamburg-Hamm | 17 | 0.1% | |
| HAMBURG | 15 | 0.1% | |
| Hamburg-Lokstedt | 14 | 0.1% | |
| Neugraben-Fischbek | 13 | 0.1% | |
| Hamburg / Harburg | 12 | 0.1% | |
| hamburg | 12 | 0.1% | |
| Other values (336) | 747 | 6.0% |
Length
| Max length | 50 |
|---|---|
| Median length | 7 |
| Mean length | 7.74896 |
| Min length | 1 |
postcode
Real number (ℝ≥0)
| Distinct count | 134 |
|---|---|
| Unique (%) | 1.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 21745.05856 |
|---|---|
| Minimum | 2103 |
| Maximum | 27661 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 2103 |
|---|---|
| 5-th percentile | 20149 |
| Q1 | 21073 |
| median | 22117 |
| Q3 | 22399 |
| 95-th percentile | 22761.1 |
| Maximum | 27661 |
| Range | 25558 |
| Interquartile range (IQR) | 1326 |
Descriptive statistics
| Standard deviation | 886.6528744 |
|---|---|
| Coefficient of variation (CV) | 0.04077491316 |
| Kurtosis | 19.84722492 |
| Mean | 21745.05856 |
| Median Absolute Deviation (MAD) | 410 |
| Skewness | -1.632490996 |
| Sum | 271813232 |
| Variance | 786153.3197 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 21073 | 346 | 2.8% | |
| 21075 | 278 | 2.2% | |
| 20457 | 271 | 2.2% | |
| 20251 | 253 | 2.0% | |
| 22303 | 252 | 2.0% | |
| 22041 | 230 | 1.8% | |
| 20535 | 219 | 1.8% | |
| 22529 | 216 | 1.7% | |
| 22299 | 210 | 1.7% | |
| 22083 | 206 | 1.6% | |
| Other values (124) | 10019 | 80.2% |
| Value | Count | Frequency (%) | |
| 2103 | 1 | < 0.1% | |
| 11111 | 1 | < 0.1% | |
| 20085 | 1 | < 0.1% | |
| 20095 | 19 | 0.2% | |
| 20097 | 137 | 1.1% |
| Value | Count | Frequency (%) | |
| 27661 | 1 | < 0.1% | |
| 23564 | 1 | < 0.1% | |
| 22999 | 3 | < 0.1% | |
| 22807 | 1 | < 0.1% | |
| 22801 | 1 | < 0.1% |
| Distinct count | 54 |
|---|---|
| Unique (%) | 0.5% |
| Missing | 913 |
| Missing (%) | 7.3% |
| Memory size | 97.7 KiB |
| 5 | |
|---|---|
| 1 | |
| 7 | |
| 6 | |
| 10 | 376 |
| Other values (49) | 675 |
| Value | Count | Frequency (%) | |
| 5 | 3815 | 30.5% | |
| 1 | 3019 | 24.2% | |
| 7 | 2915 | 23.3% | |
| 6 | 787 | 6.3% | |
| 10 | 376 | 3.0% | |
| 8 | 181 | 1.4% | |
| 11 | 80 | 0.6% | |
| 4 | 71 | 0.6% | |
| 17 | 57 | 0.5% | |
| 24 | 52 | 0.4% | |
| Other values (44) | 234 | 1.9% | |
| (Missing) | 913 | 7.3% |
Length
| Max length | 7 |
|---|---|
| Median length | 1 |
| Mean length | 1.216 |
| Min length | 1 |
| Distinct count | 7 |
|---|---|
| Unique (%) | 0.1% |
| Missing | 7722 |
| Missing (%) | 61.8% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 1.5663457513604018 |
|---|---|
| Minimum | 0.0 |
| Maximum | 6.0 |
| Zeros | 12 |
| Zeros (%) | 0.1% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 1 |
| Q1 | 1 |
| median | 1 |
| Q3 | 2 |
| 95-th percentile | 3 |
| Maximum | 6 |
| Range | 6 |
| Interquartile range (IQR) | 1 |
Descriptive statistics
| Standard deviation | 0.7407892861 |
|---|---|
| Coefficient of variation (CV) | 0.4729411022 |
| Kurtosis | 1.414323625 |
| Mean | 1.566345751 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 1.211701033 |
| Sum | 7484 |
| Variance | 0.5487687663 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 1 | 2657 | 21.3% | |
| 2 | 1591 | 12.7% | |
| 3 | 438 | 3.5% | |
| 4 | 70 | 0.6% | |
| 0 | 12 | 0.1% | |
| 5 | 9 | 0.1% | |
| 6 | 1 | < 0.1% | |
| (Missing) | 7722 | 61.8% |
| Value | Count | Frequency (%) | |
| 0 | 12 | 0.1% | |
| 1 | 2657 | 21.3% | |
| 2 | 1591 | 12.7% | |
| 3 | 438 | 3.5% | |
| 4 | 70 | 0.6% |
| Value | Count | Frequency (%) | |
| 6 | 1 | < 0.1% | |
| 5 | 9 | 0.1% | |
| 4 | 70 | 0.6% | |
| 3 | 438 | 3.5% | |
| 2 | 1591 | 12.7% |
rent_per_square_meter
Real number (ℝ≥0)
| Distinct count | 1627 |
|---|---|
| Unique (%) | 13.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 14.55844416 |
|---|---|
| Minimum | 6.0 |
| Maximum | 35.496 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 6 |
|---|---|
| 5-th percentile | 8.328 |
| Q1 | 11.592 |
| median | 14.04 |
| Q3 | 16.872 |
| 95-th percentile | 22.3806 |
| Maximum | 35.496 |
| Range | 29.496 |
| Interquartile range (IQR) | 5.28 |
Descriptive statistics
| Standard deviation | 4.313337516 |
|---|---|
| Coefficient of variation (CV) | 0.2962773679 |
| Kurtosis | 1.668225129 |
| Mean | 14.55844416 |
| Median Absolute Deviation (MAD) | 2.64 |
| Skewness | 0.9190030915 |
| Sum | 181980.552 |
| Variance | 18.60488052 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 12 | 271 | 2.2% | |
| 13.2 | 170 | 1.4% | |
| 14.4 | 158 | 1.3% | |
| 18 | 142 | 1.1% | |
| 16.8 | 126 | 1.0% | |
| 15 | 124 | 1.0% | |
| 15.6 | 102 | 0.8% | |
| 13.8 | 96 | 0.8% | |
| 10.8 | 90 | 0.7% | |
| 12.6 | 89 | 0.7% | |
| Other values (1617) | 11132 | 89.1% |
| Value | Count | Frequency (%) | |
| 6 | 7 | 0.1% | |
| 6.06 | 1 | < 0.1% | |
| 6.084 | 2 | < 0.1% | |
| 6.096 | 1 | < 0.1% | |
| 6.144 | 1 | < 0.1% |
| Value | Count | Frequency (%) | |
| 35.496 | 1 | < 0.1% | |
| 35.4 | 2 | < 0.1% | |
| 35.22 | 1 | < 0.1% | |
| 35.196 | 1 | < 0.1% | |
| 35.028 | 1 | < 0.1% |
publish_date
Categorical
| Distinct count | 41 |
|---|---|
| Unique (%) | 0.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 97.7 KiB |
| 2019-06-30 22:00:00 | 735 |
|---|---|
| 2019-01-31 23:00:00 | 605 |
| 2019-05-30 22:00:00 | 555 |
| 2019-03-28 23:00:00 | 550 |
| 2019-04-30 22:00:00 | 537 |
| Other values (36) |
| Value | Count | Frequency (%) | |
| 2019-06-30 22:00:00 | 735 | 5.9% | |
| 2019-01-31 23:00:00 | 605 | 4.8% | |
| 2019-05-30 22:00:00 | 555 | 4.4% | |
| 2019-03-28 23:00:00 | 550 | 4.4% | |
| 2019-04-30 22:00:00 | 537 | 4.3% | |
| 2019-02-28 23:00:00 | 518 | 4.1% | |
| 2018-05-30 22:00:00 | 401 | 3.2% | |
| 2017-01-31 23:00:00 | 378 | 3.0% | |
| 2018-09-30 22:00:00 | 355 | 2.8% | |
| 2018-08-31 22:00:00 | 346 | 2.8% | |
| Other values (31) | 7520 | 60.2% |
Length
| Max length | 19 |
|---|---|
| Median length | 19 |
| Mean length | 19 |
| Min length | 19 |
| Distinct count | 9830 |
|---|---|
| Unique (%) | 79.1% |
| Missing | 80 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 53.57021930800015 |
|---|---|
| Minimum | 53.4006907643781 |
| Maximum | 53.71090018137016 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 53.40069076 |
|---|---|
| 5-th percentile | 53.45954298 |
| Q1 | 53.55168885 |
| median | 53.57755594 |
| Q3 | 53.59919823 |
| 95-th percentile | 53.6483501 |
| Maximum | 53.71090018 |
| Range | 0.310209417 |
| Interquartile range (IQR) | 0.04750937432 |
Descriptive statistics
| Standard deviation | 0.05181590098 |
|---|---|
| Coefficient of variation (CV) | 0.0009672519854 |
| Kurtosis | 0.5508657812 |
| Mean | 53.57021931 |
| Median Absolute Deviation (MAD) | 0.02385509915 |
| Skewness | -0.6770937638 |
| Sum | 665342.1238 |
| Variance | 0.002684887595 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 53.54828795 | 33 | 0.3% | |
| 53.67406329 | 29 | 0.2% | |
| 53.5472869 | 28 | 0.2% | |
| 53.62552647 | 26 | 0.2% | |
| 53.54561824 | 20 | 0.2% | |
| 53.59771557 | 20 | 0.2% | |
| 53.65769505 | 18 | 0.1% | |
| 53.54353368 | 18 | 0.1% | |
| 53.47859491 | 16 | 0.1% | |
| 53.48295341 | 15 | 0.1% | |
| Other values (9820) | 12197 | 97.6% | |
| (Missing) | 80 | 0.6% |
| Value | Count | Frequency (%) | |
| 53.40069076 | 1 | < 0.1% | |
| 53.40092361 | 1 | < 0.1% | |
| 53.40187556 | 1 | < 0.1% | |
| 53.40296413 | 1 | < 0.1% | |
| 53.40644199 | 1 | < 0.1% |
| Value | Count | Frequency (%) | |
| 53.71090018 | 1 | < 0.1% | |
| 53.71037226 | 1 | < 0.1% | |
| 53.70942144 | 1 | < 0.1% | |
| 53.70885826 | 1 | < 0.1% | |
| 53.70884639 | 1 | < 0.1% |
| Distinct count | 9830 |
|---|---|
| Unique (%) | 79.1% |
| Missing | 80 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 10.008663586462754 |
|---|---|
| Minimum | 9.73918113969377 |
| Maximum | 10.291816099465922 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 97.7 KiB |
Quantile statistics
| Minimum | 9.73918114 |
|---|---|
| 5-th percentile | 9.861395543 |
| Q1 | 9.956471245 |
| median | 10.00631999 |
| Q3 | 10.06083863 |
| 95-th percentile | 10.16544689 |
| Maximum | 10.2918161 |
| Range | 0.5526349598 |
| Interquartile range (IQR) | 0.1043673825 |
Descriptive statistics
| Standard deviation | 0.08916361765 |
|---|---|
| Coefficient of variation (CV) | 0.008908643684 |
| Kurtosis | 0.3347149986 |
| Mean | 10.00866359 |
| Median Absolute Deviation (MAD) | 0.0518878108 |
| Skewness | 0.02545852981 |
| Sum | 124307.6017 |
| Variance | 0.007950150712 |
Histogram with fixed size bins (bins=10)
| Value | Count | Frequency (%) | |
| 10.01578518 | 33 | 0.3% | |
| 10.00737819 | 29 | 0.2% | |
| 10.000673 | 28 | 0.2% | |
| 10.15708566 | 26 | 0.2% | |
| 9.995743041 | 20 | 0.2% | |
| 10.02009737 | 20 | 0.2% | |
| 10.01568625 | 18 | 0.1% | |
| 9.995090601 | 18 | 0.1% | |
| 10.20442725 | 16 | 0.1% | |
| 10.20209525 | 15 | 0.1% | |
| Other values (9820) | 12197 | 97.6% | |
| (Missing) | 80 | 0.6% |
| Value | Count | Frequency (%) | |
| 9.73918114 | 1 | < 0.1% | |
| 9.743734819 | 1 | < 0.1% | |
| 9.743905026 | 1 | < 0.1% | |
| 9.744161914 | 1 | < 0.1% | |
| 9.744302918 | 1 | < 0.1% |
| Value | Count | Frequency (%) | |
| 10.2918161 | 1 | < 0.1% | |
| 10.28021482 | 1 | < 0.1% | |
| 10.27925659 | 1 | < 0.1% | |
| 10.27629233 | 1 | < 0.1% | |
| 10.26705669 | 1 | < 0.1% |
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.Cramér's V (φc)
Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.First rows
| living_space | rooms | cold_rent | construction_year | quarter | lambert_poistion_x | lambert_poistion_y | city | postcode | heating_type | number_of_bedrooms | rent_per_square_meter | publish_date | latitude | longitude | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 116.4 | 4.5 | 1453.200 | 1976.0 | Farmsen-Berne | 7967.0 | 2625150.0 | Hamburg | 22159 | 6 | NaN | 14.976 | 2019-05-30 22:00:00 | 53.597793 | 10.121997 |
| 1 | 78.0 | 3.0 | 819.600 | NaN | Wandsbek | 5628.0 | 2623928.0 | Hamburg | 22047 | 1 | NaN | 12.612 | 2019-01-31 23:00:00 | 53.586691 | 10.086159 |
| 2 | 62.4 | 3.5 | 504.000 | NaN | Wilstorf | -239.0 | 2608361.0 | Hamburg | 21079 | 1 | NaN | 9.696 | 2019-01-31 23:00:00 | 53.444908 | 9.996353 |
| 3 | 98.4 | 3.5 | 1131.600 | 1982.0 | Rahlstedt | 9481.0 | 2628105.0 | Hamburg | 22145 | 1 | NaN | 13.800 | 2019-04-30 22:00:00 | 53.624685 | 10.145269 |
| 4 | 144.0 | 3.5 | 2280.000 | NaN | Blankenese | -13093.0 | 2620974.0 | Hamburg | 22587 | 5 | 2.0 | 18.996 | 2019-03-28 23:00:00 | 53.559652 | 9.799682 |
| 5 | 97.8 | 3.5 | 1128.000 | 2021.0 | Langenhorn | 369.0 | 2631379.0 | Hamburg | 22419 | 5 | NaN | 13.836 | 2019-02-28 23:00:00 | 53.654590 | 10.005658 |
| 6 | 60.0 | 2.5 | 660.000 | 1964.0 | Neugraben-Fischbek | -9224.0 | 2612187.0 | Hamburg | 21147 | 6 | 1.0 | 13.200 | 2019-01-31 23:00:00 | 53.479685 | 9.859130 |
| 7 | 78.0 | 2.5 | 573.768 | 1970.0 | Marmstorf | -2662.0 | 2607988.0 | Hamburg | 21077 | 7 | NaN | 8.832 | 2019-06-30 22:00:00 | 53.441503 | 9.959381 |
| 8 | 61.2 | 2.5 | 807.600 | NaN | Barmbek-Nord | 3091.0 | 2625603.0 | Hamburg | 22307 | 1 | NaN | 15.840 | 2019-04-30 22:00:00 | 53.601970 | 10.047336 |
| 9 | 60.0 | 2.5 | 660.000 | 1964.0 | Neugraben-Fischbek | -9224.0 | 2612187.0 | Hamburg | 21147 | 6 | 1.0 | 13.200 | 2019-01-31 23:00:00 | 53.479685 | 9.859130 |
Last rows
| living_space | rooms | cold_rent | construction_year | quarter | lambert_poistion_x | lambert_poistion_y | city | postcode | heating_type | number_of_bedrooms | rent_per_square_meter | publish_date | latitude | longitude | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 12490 | 256.704 | 8.0 | 2916.000 | 1916.0 | Groß Flottbek | -7369.0 | 2621225.0 | Hamburg | 22607 | NaN | NaN | 13.632 | 2016-05-30 22:00:00 | 53.562048 | 9.887251 |
| 12491 | 65.184 | 2.5 | 900.000 | 1934.0 | Hamm-Süd | 3812.0 | 2619894.0 | Hamburg | 20537 | 1 | NaN | 16.572 | 2016-06-30 22:00:00 | 53.549961 | 10.058309 |
| 12492 | 86.400 | 3.5 | 508.200 | 1970.0 | Marmstorf | -2507.0 | 2608023.0 | Hamburg | 21077 | 7 | NaN | 7.056 | 2016-04-30 22:00:00 | 53.441823 | 9.961746 |
| 12493 | 74.400 | 2.5 | 912.000 | 1989.0 | Wellingsbüttel | 5623.0 | 2630277.0 | Hamburg | 22391 | 5 | NaN | 14.712 | 2016-08-31 22:00:00 | 53.644523 | 10.086195 |
| 12494 | 59.640 | 2.5 | 399.588 | 1957.0 | Heimfeld | -3146.0 | 2611160.0 | Hamburg | 21075 | 5 | NaN | 8.040 | 2016-10-30 22:00:00 | 53.470399 | 9.951964 |
| 12495 | 78.840 | 3.5 | 684.000 | 1962.0 | Rahlstedt | 8515.0 | 2625898.0 | Hamburg | 22147 | 5 | NaN | 10.416 | 2016-01-31 23:00:00 | 53.604598 | 10.130409 |
| 12496 | 60.000 | 2.5 | 930.000 | 1874.0 | Barmbek-Süd | 1937.0 | 2622714.0 | Hamburg | 22083 | NaN | 1.0 | 18.600 | 2016-02-29 23:00:00 | 53.575659 | 10.029646 |
| 12497 | 92.940 | 2.5 | 606.000 | NaN | St. Pauli | -2575.0 | 2619807.0 | Hamburg | 20359 | 1 | NaN | 7.824 | 2016-10-30 22:00:00 | 53.549175 | 9.960613 |
| 12498 | 69.540 | 2.5 | 748.200 | 1939.0 | Winterhude | 1231.0 | 2624265.0 | Hamburg | 22303 | 7 | 1.0 | 12.912 | 2016-03-29 23:00:00 | 53.589789 | 10.018847 |
| 12499 | 73.200 | 3.0 | 518.532 | 1958.0 | Heimfeld | -2245.0 | 2610261.0 | Hamburg | 21075 | 5 | NaN | 8.496 | 2016-06-30 22:00:00 | 53.462213 | 9.965728 |
Most frequent
| living_space | rooms | cold_rent | construction_year | quarter | lambert_poistion_x | lambert_poistion_y | city | postcode | heating_type | number_of_bedrooms | rent_per_square_meter | publish_date | latitude | longitude | count | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | 59.352 | 3.0 | 742.800 | 1961.0 | Ohlsdorf | 2088.0 | 2626963.0 | Hamburg | 22337 | 5 | 2.0 | 15.024 | 2017-02-28 23:00:00 | 53.614363 | 10.031985 | 3 |
| 0 | 51.372 | 2.5 | 328.764 | 2022.0 | Othmarschen | -6435.0 | 2620790.0 | Hamburg | 22763 | 7 | 1.0 | 7.680 | 2018-07-30 22:00:00 | 53.558097 | 9.901550 | 2 |
| 1 | 53.640 | 1.5 | 1421.460 | 2022.0 | HafenCity | -321.0 | 2619187.0 | Hamburg, HafenCity | 20457 | 7 | 1.0 | 31.800 | 2019-03-28 23:00:00 | 53.543534 | 9.995091 | 2 |
| 2 | 54.000 | 1.5 | 745.200 | 1955.0 | Horn | 5265.0 | 2620184.0 | Hamburg | 22111 | 5 | 1.0 | 16.560 | 2019-02-28 23:00:00 | 53.552590 | 10.080540 | 2 |
| 3 | 55.200 | 1.5 | 972.000 | 2020.0 | Hoheluft-West | -1910.0 | 2623459.0 | Hamburg | 20253 | 5 | 1.0 | 21.132 | 2017-08-31 22:00:00 | 53.582445 | 9.970763 | 2 |
| 5 | 60.000 | 2.5 | 660.000 | 1964.0 | Neugraben-Fischbek | -9224.0 | 2612187.0 | Hamburg | 21147 | 6 | 1.0 | 13.200 | 2019-01-31 23:00:00 | 53.479685 | 9.859130 | 2 |
| 6 | 60.000 | 2.5 | 750.000 | 1878.0 | Borgfelde | 1896.0 | 2620652.0 | Hamburg | 20535 | 19 | 1.0 | 15.000 | 2019-05-30 22:00:00 | 53.556876 | 10.029006 | 2 |
| 7 | 65.400 | 2.5 | 552.000 | 1897.0 | Wilhelmsburg | 1385.0 | 2615541.0 | Hamburg | 21109 | 5 | 1.0 | 10.128 | 2018-09-30 22:00:00 | 53.510318 | 10.021166 | 2 |
| 8 | 66.000 | 2.5 | 660.000 | 1998.0 | Wandsbek | 5253.0 | 2623306.0 | Hamburg | 22041 | 5 | 1.0 | 12.000 | 2019-05-30 22:00:00 | 53.581029 | 10.080408 | 2 |
| 9 | 66.000 | 2.5 | 890.400 | 2019.0 | Niendorf | -3971.0 | 2628213.0 | Hamburg | 22459 | 5 | 1.0 | 16.188 | 2017-03-28 23:00:00 | 53.625738 | 9.939154 | 2 |